Effect of internet use for health information and internet addiction on adolescents female high school’ health lifestyle
Bibliographic record
Abstract
Background and objective: There is not enough evidence linking attitudes toward using the Internet to gather health information and adolescents’ lifestyles. The objective of this study is to assess the effect of Internet use for gathering health information and Internet addiction on adolescents’ health lifestyles in Saudi Arabia.Methods: A descriptive correlational cross-sectional design was utilized to collect data from a convenience sample of 456 high-school-aged female adolescents, who completed self-administered questionnaires consisting of demographic data, attitudes toward Internet use, Internet use for seeking health information, Internet use to communicate about health, Internet addiction, and adolescent health lifestyles.Results: The adolescent female high school students’ average age was 16.88 years (SD = 1.05); Regression analyses revealed that the main effects of students’ attitudes toward the Internet, along with how using the Internet to seek health information and to communicate about health, and Internet addiction significantly (p < .001) affected these female high school students’ lifestyles subscales. However, some predictors had varied effects on lifestyle subscales.Conclusions: The general consensus of the research about Internet use among young people to date shows that adolescents use the Internet to communicate about their own health problems, but they do not address all of the dimensions of healthy lifestyle. This study will help identify lifestyle risk factors among adolescent female high school students, such as malnutrition, physical inactivity, not taking full responsibility for one’s health and not communicating enough about one’s health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".